Blood metabolites and gastric cancer risk: A bidirectional 2-sample Mendelian randomization study

Abstract

Notably, metabolic dysregulation stands as a prominent characteristic of cancer. The identification of biomarkers through blood metabolomics presents a novel approach for the diagnosis and treatment of gastric cancer. We performed a 2-sample Mendelian randomization (MR) analysis to assess the causality from genetically proxied 486 blood metabolites to gastric cancer. In this study, MR analysis was employed to assess the correlation between 486 serum metabolites and gastric cancer. Five different methods, namely inverse-variance weighting, MR-Egger method, weighted median method, simple mode method, and weighted mode method, were utilized for evaluation. Sensitivity analysis was conducted, encompassing heterogeneity testing, horizontal pleiotropy testing, and leave-one-out testing. Furthermore, the study encompassed linkage disequilibrium score (LDSC) genetic association and directionality assessment, metabolic pathway analysis, and reverse MR analysis. The findings revealed the presence of 21 metabolites, comprising 14 known metabolites and 7 unidentified metabolites that potentially play a causal role in gastric cancer. The reverse MR and directional assessment indicated the absence of reverse causality between gastric cancer and the candidate metabolites. Moreover, the LDSC genetic association solely identified a genetic association between gastric cancer and the unknown metabolite X-11315. Additionally, the metabolic pathway analysis identified 3 pathways that may be implicated in the development of the disease. We observed negative correlations between 12 serum metabolites and the risk of gastric cancer, while 9 serum metabolites showed positive correlations. Notably, 3-methyl-2-oxovalerate exhibited promising therapeutic potential, whereas 2-aminobutyrate displayed a higher risk factor. The integration of genomics and metabolomics in our investigation offers novel insights into the underlying mechanisms of gastric cancer, thereby holding significant implications for the screening and prevention of this disease.

Keywords: Mendelian randomization; biomarkers; blood metabolites; gastric cancer.

Figure 1.

Overview of present MR analyses and assumptions. GWAS = genome-wide association studies, IV = instrumental variable, IVW = inverse-variance weighting, LDSC = linkage disequilibrium score, MR = Mendelian randomization, SM = simple mode method, SNPs = single nucleotide polymorphisms, WME = weighted median method, WMO = weighted mode method.

Figure 2.

Mendelian randomization results for blood metabolites and the risks of gastric cancer based on the IVW method. The dashed red and solid blue lines indicate MR ORs and 95% CIs. The blue dots represent MR. CI = confidence interval, IVW = inverse-variance weighting, MR = Mendelian randomization, OR = odds ratio.